[Ginsenoside Rg_1 ameliorates OGD/R-induced PC12 cell injury by inhibiting autography via IRE1-JNK-CHOP pathway].

This study investigated the protective effect of ginsenoside Rg_1(GRg_1) on oxygen and glucose deprivation/reoxygenation(OGD/R)-injured rat adrenal pheochromocytoma(PC12) cells and whether the underlying mechanism was related to the regulation of inositol-requiring enzyme 1(IRE1)-c-Jun N-terminal kinase(JNK)-C/EBP homologous protein(CHOP) signaling pathway. An OGD/R model was established in PC12 cells, and PC12 cells were randomly classified into control, model, OGD/R+GRg_1(0.1, 1, 10 µmol·L~(-1)), OGD/R+GRg_1+rapamycin(autophagy agonist), OGD/R+GRg_1+3-methyladenine(3-MA,autophagy inhibitor), OGD/R+GRg_1+tunicamycin(endoplasmic reticulum stress agonist), OGD/R+GRg_1+4-phenylbutyric acid(4-PBA, endoplasmic reticulum stress inhibitor), and OGD/R+GRg_1+3,5-dibromosalicylaldehyde(DBSA, IRE1 inhibitor) groups. Except the control group, the other groups were subjected to OGD/R treatment, i.e., oxygen and glucose deprivation for 6 h followed by reoxygenation for 6 h. Cell viability was detected by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl tetrazolium bromide(MTT) assay. Apoptosis was detected by Hoechst 33342 staining, and the fluorescence intensity of autophagosomes by the monodansylcadaverine(MDC) assay. Western blot was employed to determine the expression of autophagy-related proteins(Beclin1, LC3-Ⅱ, and p62) and the pathway-related proteins [IRE1, p-IRE1, JNK, p-JNK, glucose-regulated protein 78(GRP78), and CHOP]. The results showed that GRg_1 dose-dependently increased the viability of PC12 cells and down-regulated the expression of Beclin1, LC3-Ⅱ, p-IRE1, p-JNK, GRP78, and CHOP, compared with the model group. Furthermore, GRg_1 decreased the apoptosis rate and MDC fluorescence intensity and up-regulated the expression of p62 protein. Compared with the OGD/R+GRg_1(10 µmol·L~(-1)) group, OGD/R+GRg_1+rapamycin and OGD/R+GRg_1+tunicamycin groups showed increased apoptosis rate and MDC fluorescence intensity, up-regulated protein levels of Beclin1, LC3-Ⅱ, p-IRE1, p-JNK, GRP78, and CHOP, decreased relative cell survival rate, and down-regulated protein level of p62. The 3-MA, 4-PBA, and DBSA groups exerted the opposite effects. Taken together, GRg_1 may ameliorate OGD/R-induced PC12 cell injury by inhibiting autophagy via the IRE1-JNK-CHOP pathway.

Laser direct overall water splitting for H2 and H2O2 production.

Hydrogen (H2) and hydrogen peroxide (H2O2) play crucial roles as energy carriers and raw materials for industrial production. However, the current techniques for H2 and H2O2 production rely on complex catalysts and involve multiple intermediate steps. In this study, we present a straightforward, environmentally friendly, and highly efficient laser-induced conversion method for overall water splitting to simultaneously generate H2 and H2O2 at ambient conditions without any catalysts. The laser direct overall water splitting approach achieves an impressive light-to-hydrogen energy conversion efficiency of 2.1%, with H2 production rates of 2.2 mmol/h and H2O2 production rates of 65 µM/h in a limited reaction area (1 mm2) within a short real reaction time (0.36 ms/h). Furthermore, we elucidate the underlying physics and chemistry behind the laser-induced water splitting to produce H2 and H2O2. The laser-induced cavitation bubbles create an optimal microenvironment for water-splitting reactions because of the transient high temperatures (104 K) surpassing the chemical barrier required. Additionally, their rapid cooling rate (1010 K/s) hinders reverse reactions and facilitates H2O2 retention. Finally, upon bubble collapse, H2 is released while H2O2 remains dissolved in the water. Moreover, a preliminary amplification experiment demonstrates the potential industrial applications of this laser chemistry. These findings highlight that laser-based production of H2 and H2O2 from water holds promise as a straightforward, environmentally friendly, and efficient approach on an industrial scale beyond conventional chemical catalysis.

Graph neural network recommendation algorithm based on improved dual tower model.

In this era of information explosion, recommendation systems play a key role in helping users to uncover content of interest among massive amounts of information. Pursuing a breadth of recall while maintaining accuracy is a core challenge for current recommendation systems. In this paper, we propose a new recommendation algorithm model, the interactive higher-order dual tower (IHDT), which improves current models by adding interactivity and higher-order feature learning between the dual tower neural networks. A heterogeneous graph is constructed containing different types of nodes, such as users, items, and attributes, extracting richer feature representations through meta-paths. To achieve feature interaction, an interactive learning mechanism is introduced to inject relevant features between the user and project towers. Additionally, this method utilizes graph convolutional networks for higher-order feature learning, pooling the node embeddings of the twin towers to obtain enhanced end-user and item representations. IHDT was evaluated on the MovieLens dataset and outperformed multiple baseline methods. Ablation experiments verified the contribution of interactive learning and high-order GCN components.

Network pharmacology-based approach to understand the effect and mechanism of chrysophanol against cognitive impairment in Wilson disease.

Wilson disease (WD) is a rare hereditary copper metabolism disorder, wherein cognitive impairment is a common clinical symptom. Chrysophanol (CHR) is an active compound with neuroprotective effects. The study aims to investigate the neuroprotective effect of CHR in WD and attempted to understand the potential mechanisms. Network pharmacology analysis was applied to predict the core target genes of CHR against cognitive impairment in WD. The rats fed with copper-laden diet for 12 weeks, and the effect of CHR on the copper content in liver and 24-h urine, the learning and memory ability, the morphological changes and the apoptosis level of neurons in hippocampal CA1 region, the expression level of Bax, Bcl-2, Cleaved Caspase-3, p-PI3K, PI3K, p-AKT, and AKT proteins were detected. Network pharmacology analysis showed that cell apoptosis and PI3K-AKT signaling pathway might be the main participants in CHR against cognitive impairment in WD. The experiments showed that CHR could reduce the copper content in liver, increase the copper content in 24-h urine, improve the ability of the learning and memory, alleviate the damage and apoptosis level of hippocampal neurons, down-regulate the expression of Bax, Cleaved Caspase-3, and up-regulate the expressions of Bcl-2, p-PI3K/PI3K, p-AKT/AKT. These results suggested that CHR could alleviate cognitive impairment in WD by inhibiting cell apoptosis and triggering the PI3K-AKT signaling pathway.

Spine MRI image segmentation method based on ASPP and U-Net network.

The spine is one of the most important structures in the human body, serving to support the body, organs, protect nerves, etc. Medical image segmentation for the spine can help doctors in their clinical practice for rapid decision making, surgery planning, skeletal health diagnosis, etc. The current difficulty is mainly the poor segmentation accuracy of skeletal Magnetic Resonance Imaging (MRI) images. To address the problem, we propose a spine MRI image segmentation method, Atrous Spatial Pyramid Pooling (ASPP)-U-shaped network (UNet), which combines an ASPP structure with a U-Net network. This approach improved the network feature extraction by introducing an ASPP structure into the U-Net network down-sampling structure. The medical image segmentation models are trained and tested on publicly available datasets and obtained the Dice coefficient and Mean Intersection over Union coefficients with 0.866 and 0.755, respectively. The experimental results show that ASPP-UNet has higher accuracy for spine MRI image segmentation compared with other mainstream networks.

Chrysophanol improves memory impairment and cell injury by reducing the level of ferroptosis in Aß25-35 treated rat and PC12 cells.

Alzheimer's disease (AD) is a common age-related chronic and neurodegenerative disease that has become a global health problem. AD pathogenesis is complex, and the clinical efficacy of commonly used anti-AD drugs is suboptimal. Recent research has revealed a close association between AD-induced damage and the activation of ferroptosis signaling pathways. Chrysophanol (CHR) the principal medicinal component of Rhubarb, has been reported to have anti-AD effects and can reduce ROS levels in AD-damaged models. AD has been linked to the activation of ferroptosis signaling pathways, which has an important feature of higher levels of reactive oxygen species (ROS). Therefore, the present study explored whether CHR had an anti-AD effect by regulating the ferroptosis levels in AD injury models. Morris water maze, novel object recognition test, Y-maze test, Hematoxylin-eosin (H&E) staining, western blotting, ROS measurement, GPx activity measurement, LPO measurement, transmission electron microscopy, live/dead cell staining were used to investigate the changes in spatial memory level and ferroptosis level in AD model, and the intervention effect of CHR. CHR improved the spatial memory level of AD rat models, reduced the level of hippocampal neuron damage, and improved the survival rate of PC12 cells damaged by ß-amyloid (Aß). Meanwhile, CHR increased glutathione peroxidase-4 (GPX4) protein expression, GPx activity, and GSH, decreased ROS and LPO levels in AD rat models and Aß-damaged PC12 cells, and improved mitochondrial pathological damage. Our findings suggest that CHR may play a protective role in AD injury by lowering ferroptosis levels, which may provide a potential pathway for developing drugs for AD. However, the mechanism of CHR's role requires further investigation.

Phosphorylation of MAP 1A regulates hyperphosphorylation of Tau in Alzheimer's disease model.

BACKGROUND AND PURPOSE: Hyperphosphorylation of Tau is one of the important pathological features of Alzheimer's disease (AD). Therefore, studying the mechanisms behind Tau hyperphosphorylation is crucial in exploring the pathogenesis of neurological damage in AD. METHODS: In this study, after the establishment of rat models of AD, quantitative phosphoproteomics and proteomics were performed to identify proteins, showing that phosphorylation of microtubule associated protein 1A (MAP 1A) was lower in the model group. Western blot confirmed the changes of MAP 1A in the SD rats, APP/PS1 transgenic mice and cell AD models. To further study the molecular mechanism of recombinant MAP 1A phosphorylation affecting Tau phosphorylation, interfering siRNA-MAP 1A and protein immunoprecipitation reaction analysis were performed in AD cell models. RESULTS: Cyclin-dependent kinase 5 (CDK5) showed reduced binding to MAP 1A and increased binding to Tau, resulting in a decrease in phosphorylated MAP 1A (p-MAP 1A) and an increase in phosphorylated Tau (p-Tau), and MAP 1A silencing promoted binding of CDK5-Tau and increased Tau phosphorylation, thereby reducing the cell survival rate. CONCLUSIONS: In summary, we found that p-MAP 1A downregulation associated with p-Tau upregulation was due to their altered binding forces to CDK5, and MAP 1A could enhance autophosphorylation by competitive binding to CDK5 and antagonise Tau phosphorylation. This leads to neuronal protection and reducing tissue damage levels in AD, which can help better understand the mechanisms of AD pathogenesis.

Cell-type-specific co-expression inference from single cell RNA-sequencing data.

The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. For this task, the high sequencing depth variations and measurement errors in scRNA-seq data present two significant challenges, and they have not been adequately addressed by existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, that explicitly models sequencing depth variations and measurement errors in scRNA-seq data. Systematic evaluations show that most existing methods suffered from inflated false positives as well as biased co-expression estimates and clustering analysis, whereas CS-CORE gave accurate estimates in these experiments. When applied to scRNA-seq data from postmortem brain samples from Alzheimer's disease patients/controls and blood samples from COVID-19 patients/controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from existing methods.

Comprehensive analysis of the coding and non-coding RNA transcriptome expression profiles of hippocampus tissue in tx-J animal model of Wilson's disease.

Wilson's disease (WD) is an autosomal recessive disorder with a genetic basis. The predominant non-motor symptom of WD is cognitive dysfunction, although the specific genetic regulatory mechanism remains unclear. Tx-J mice, with an 82% sequence homology of the ATP7B gene to the human gene, are considered the most suitable model for WD. This study employs deep sequencing to investigate the differences in RNA transcript profiles, both coding and non-coding, as well as the functional characteristics of the regulatory network involved in WD cognitive impairment. The cognitive function of tx-J mice was evaluated using the Water Maze Test (WMT). Long non-coding RNA (lncRNA), circular RNA (circRNA), and messenger RNA (mRNA) profiles were analyzed in the hippocampal tissue of tx-J mice to identify differentially expressed RNAs (DE-RNAs). Subsequently, the DE-RNAs were used to construct protein-protein interaction (PPI) networks, as well as DE-circRNAs and lncRNAs-associated competing endogenous RNA (ceRNA) expression networks, and coding-noncoding co-expression (CNC) networks. To elucidate their biological functions and pathways, the PPI and ceRNA networks were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A total of 361 differentially expressed mRNAs (DE-mRNAs), comprising 193 up-regulated and 168 down-regulated mRNAs, 2627 differentially expressed long non-coding RNAs (DE-lncRNAs), consisting of 1270 up-regulated and 1357 down-regulated lncRNAs, and 99 differentially expressed circular RNAs (DE-circRNAs), consisting of 68 up-regulated and 31 down-regulated circRNAs, were observed in the tx-J mice group when compared to the control mice group. Gene Ontology (GO) and pathway analyses revealed that DE-mRNAs were enriched in cellular processes, calcium signaling pathways, and mRNA surveillance pathways. In contrast, the DE-circRNAs-associated competing endogenous RNA (ceRNA) network was enriched for covalent chromatin modification, histone modification, and axon guidance, whereas the DE-lncRNAs-associated ceRNA network was enriched for dendritic spine, regulation of cell morphogenesis involved in differentiation, and mRNA surveillance pathway. The study presented the expression profiles of lncRNA, circRNA, and mRNA in the hippocampal tissue of tx-J mice. Furthermore, the study constructed PPI, ceRNA, and CNC expression networks. The findings are significant in comprehending the function of regulatory genes in WD associated with cognitive impairment. These results also offer valuable information for the diagnosis and treatment of WD.

Antibody sequences assembly method based on weighted de Bruijn graph.

With the development of next-generation protein sequencing technologies, sequence assembly algorithm has become a key technology for de novo sequencing process. At present, the existing methods can address the assembly of an unknown single protein chain. However, for monoclonal antibodies with light and heavy chains, the assembly is still an unsolved question. To address this problem, we propose a new assembly method, DBAS, which integrates the quality scores and sequence alignment scores from de novo sequencing peptides into a weighted de Bruijn graph to assemble the final protein sequences. The established method is used to assembling sequences from two datasets with mixed light and heavy chains from antibodies. The results show that the DBAS can assemble long antibody sequences for both mixed light and heavy chains and single chains. In addition, DBAS is able to distinguish the light and heavy chains by using BLAST sequence alignment. The results show that the algorithm has good performance for both target sequence coverage and contig assembly accuracy.

Live imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo.

Stem cell differentiation requires dramatic changes in gene expression and global remodeling of chromatin architecture. How and when chromatin remodels relative to the transcriptional, behavioral, and morphological changes during differentiation remain unclear, particularly in an intact tissue context. Here, we develop a quantitative pipeline which leverages fluorescently-tagged histones and longitudinal imaging to track large-scale chromatin compaction changes within individual cells in a live mouse. Applying this pipeline to epidermal stem cells, we reveal that cell-to-cell chromatin compaction heterogeneity within the stem cell compartment emerges independent of cell cycle status, and instead is reflective of differentiation status. Chromatin compaction state gradually transitions over days as differentiating cells exit the stem cell compartment. Moreover, establishing live imaging of Keratin-10 (K10) nascent RNA, which marks the onset of stem cell differentiation, we find that Keratin-10 transcription is highly dynamic and largely precedes the global chromatin compaction changes associated with differentiation. Together, these analyses reveal that stem cell differentiation involves dynamic transcriptional states and gradual chromatin rearrangement.

Chrysophanol exerts a protective effect against Aß25-35-induced Alzheimer's disease model through regulating the ROS/TXNIP/NLRP3 pathway.

BACKGROUND: The primary pathogenic factors of Alzheimer's disease (AD) have been identified as oxidative stress, inflammatory damage, and apoptosis. Chrysophanol (CHR) has a good neuroprotective effect on AD, however, the potential mechanism of CHR remains unclear. PURPOSE: In this study, we focused on the ROS/TXNIP/NLRP3 pathway to determine whether CHR regulates oxidative stress and neuroinflammation. METHODS: D-galactose and Aß25-35 combination were used to build an in vivo model of AD, and the Y-maze test was used to evaluate the learning and memory function of rats. Morphological changes of neurons in the rat hippocampus were observed using hematoxylin and eosin (HE) staining. AD cell model was established by Aß25-35 in PC12 cells. The DCFH-DA test identified reactive oxygen species (ROS). The apoptosis rate was determined using Hoechst33258 and flow cytometry. In addition, the levels of MDA, LDH, T-SOD, CAT, and GSH in serum, cell, and cell culture supernatant were detected by colorimetric method. The protein and mRNA expressions of the targets were detected by Western blot and RT-PCR. Finally, molecular docking was used to further verify the in vivo and in vitro experimental results. RESULTS: CHR could significantly improve learning and memory impairment, reduce hippocampal neuron damage, and reduce ROS production and apoptosis in AD rats. CHR could improve the survival rate, and reduce the oxidative stress and apoptosis in the AD cell model. Moreover, CHR significantly decreased the levels of MDA and LDH, and increased the activities of T-SOD, CAT, and GSH in the AD model. Mechanically, CHR significantly reduced the protein and mRNA expression of TXNIP, NLRP3, Caspase-1, IL-1ß, and IL-18, and increase TRX. CONCLUSIONS: CHR exerts neuroprotective effects on the Aß25-35-induced AD model mainly by reducing oxidative stress and neuroinflammation, and the mechanism may be related to ROS/TXNIP/NLRP3 signaling pathway.

The effects of N6-methyladenosine RNA methylation on the nervous system.

Epitranscriptomics, also known as "RNA epigenetics", is a type of chemical modification that regulates RNA. RNA methylation is a significant discovery after DNA and histone methylation. The dynamic reversible process of m6A involves methyltransferases (writers), m6A binding proteins (readers), as well as demethylases (erasers). We summarized the current research status of m6A RNA methylation in the neural stem cells' growth, synaptic and axonal function, brain development, learning and memory, neurodegenerative diseases, and glioblastoma. This review aims to provide a theoretical basis for studying the mechanism of m6A methylation and finding its potential therapeutic targets in nervous system diseases.

Fabrication of Super-Sized Metal Inorganic-Organic Hybrid Glass with Supramolecular Network via Crystallization-Suppressing Approach.

Metal coordination compound (MCC) glasses [e.g., metal-organic framework (MOF) glass, coordination polymer glass, and metal inorganic-organic complex (MIOC) glass] are emerging members of the hybrid glass family. So far, a limited number of crystalline MCCs can be converted into glasses by melt-quenching. Here, we report a universal wet-chemistry method, by which the super-sized supramolecular MIOC glasses can be synthesized from non-meltable MOFs. Alcohol and acid were used as agents to inhibit crystallization. The MIOC glasses demonstrate unique features including high transparency, shaping capability, and anisotropic network. Directional photoluminescence with a large polarization ratio (≈47 %) was observed from samples doped with organic dyes. This crystallization-suppressing approach enables fabrication of super-sized MCC glasses, which cannot be achieved by conventional vitrification methods, and thus allows for exploring new MCC glasses possessing photonic functionalities.

Protective effect of Huangpu Tongqiao capsule against Alzheimer's disease through inhibiting the apoptosis pathway mediated by endoplasmic reticulum stress in vitro and in vivo.

Objectives: Huangpu Tongqiao Capsule (HPTQC) is a traditional Chinese medicine (TCM) that has been used to treat Alzheimer's disease (AD). This study was to explore the pharmacological action and molecular mechanism of HPTQC in the treatment of AD. Methods: The possible targets of HTPQC were predicted by the molecular docking technique. Intraperitoneal injection of D-galactose and bilateral injection of Aß25-35 in hippocampus induced AD rat model. Morris water maze was used to observe learning and memory function. The primary hippocampal neurons were induced by Aß25-35. Moreover, the apoptosis rate of hippocampal nerve cells was detected through AnnexinV/PI double standard staining. The mRNA and protein levels of GRP78, CHOP, Caspase 12, Caspase 9, and Caspase 3 were detected by PCR and western blot. Results: The prediction results suggest that HPTQC may act on GRP78. HPTQC significantly improved the learning and memory function, and decreased neuronal apoptosis in vivo and in vitro. In addition, HPTQC could decrease the mRNA and protein expression levels of GRP78, CHOP, Caspase12, Caspase9, and Caspase3, and the effect trend was consistent with the specific inhibitor of GRP78. Conclusions: HPTQC has a neuroprotective effect against AD by inhibiting the apoptosis pathway mediated by endoplasmic reticulum stress.

Cell-type-specific co-expression inference from single cell RNA-sequencing data.

The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring cell-type-specific gene co-expressions, and these issues have not been adequately addressed in the existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, built on a general expression-measurement model that explicitly accounts for sequencing depth variations and measurement errors in the observed single cell data. Systematic evaluations show that most existing methods suffer from inflated false positives and biased co-expression estimates and clustering analysis, whereas CS-CORE has appropriate false positive control, unbiased co-expression estimates, good statistical power and satisfactory performance in downstream co-expression analysis. When applied to analyze scRNA-seq data from postmortem brain samples from Alzheimer’s disease patients and controls and blood samples from COVID-19 patients and controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from other methods.

Genistein attenuates memory impairment in Alzheimer's disease via ERS-mediated apoptotic pathway in vivo and in vitro.

Genistein (GS), an isoflavone compound found in soybean, plays a neuroprotective role in Alzheimer's disease (AD). However, the mechanism of its action remains unclear. Herein, binding ability between GS and GRP78 was predicted by molecular docking, and the effect of GS in vivo and vitro were further studied. In this study, the effects of GS on learning and memory ability, changes of hippocampal neurons and ultrastructure of hippocampal CA3 region in AD rats were investigated. Besides, the protein or mRNA levels of the related proteins were detected. The results showed GS could effectively improve the learning and the memory ability, reduce the damage of hippocampal neurons, and decrease the protein or mRNA expression levels of GRP78, CHOP, Caspase-12, Cle-Caspase-9, Cle-Caspase-3, PERK, and p-PERK. Taken together, our data reveal GS has a neuroprotective effect by inhibiting the ERS-mediated apoptotic pathway, which may be a new therapeutic target for the treatment of AD.

Current Advancements in Antitumor Properties and Mechanisms of Medicinal Components in Edible Mushrooms.

Edible and medicinal fungi, a group of eukaryotic organisms with numerous varieties, including Coriolus versicolor, Ganoderma lucidum, Cordyceps sinensis, Pleurotus ostreatus, and Grifola frondosa, have been demonstrated to possess a board range of pharmaceutical properties, including anti-virus, anti-inflammation, and neuroprotection. Moreover, edible and medicinal fungi have been traditionally consumed as food to provide multiple nutrients and as drugs owing to having the activities of invigorating blood circulation, reinforcing the healthy qi, clearing away heat, and eliminating stasis for thousands of years in China. Malignant tumors, well-known as the second leading cause of death globally, accounted for nearly 10 million deaths in 2020. Thus, in-depth exploration of strategies to prevent and treat cancer is extremely urgent. A variety of studies have reported that the main bioactive components of edible and medicinal fungi, mainly polysaccharides and triterpenoids, exhibit diverse anticancer activities via multiple mechanisms, including inhibition of cell proliferation and metastasis, induction of apoptosis and autophagy, reversing multidrug resistance, and regulation of immune responses, thus suggesting their substantial potential in the prevention and treatment of cancer. Our review summarizes the research progress on the anticancer properties of edible and medicinal fungi and the underlying molecular mechanism, which may offer a better understanding of this field. Additionally, few studies have reported the safety and efficacy of extracts from edible and medicinal fungi, which may limit their clinical application. In summary, there is a need to continue to explore the use of those extracts and to further validate their safety and efficacy.

Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model.

Functional connectivity (FC) between brain region has been widely studied and linked with cognition and behavior of an individual. FC is usually defined as the correlation or partial correlation of fMRI blood oxygen level-dependent (BOLD) signals between two brain regions. Although FC has been effective to understand brain organization, it cannot reveal the direction of interactions. Many directed acyclic graph (DAG) based methods have been applied to study the directed interactions but their performance was limited by the small sample size while high dimensionality of the available data. By enforcing group regularization and utilizing samples from both case and control groups, we propose a joint DAG model to estimate the directed FC. We first demonstrate that the proposed model is efficient and accurate through a series of simulation studies. We then apply it to the case-control study of schizophrenia (SZ) with data collected from the MIND Clinical Imaging Consortium (MCIC). We have successfully identified decreased functional integration, disrupted hub structures and characteristic edges (CtEs) in SZ patients. Those findings have been confirmed by previous studies with some identified to be potential markers for SZ patients. A comparison of the results between the directed FC and undirected FC showed substantial differences in the selected features. In addition, we used the identified features based on directed FC for the classification of SZ patients and achieved better accuracy than using undirected FC or raw features, demonstrating the advantage of using directed FC for brain network analysis.